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Gan Y, Zhang Z, Liu F, Chen Z, Guo Q, Zhu Z, Ren Y. Analysis of characteristics and changes in three-dimensional spatial and temporal distribution of aerosol types in Central Asia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:172196. [PMID: 38580123 DOI: 10.1016/j.scitotenv.2024.172196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 04/01/2024] [Accepted: 04/01/2024] [Indexed: 04/07/2024]
Abstract
Atmospheric aerosol types and characteristics have regional and seasonal characteristics mainly due spatial and temporal differences in emission sources and diffuse transport conditions. We explored regional three-dimensional spatial and temporal distribution characteristics of aerosol types in Central Asia from daytime to nighttime by using long-term (2007-2021) CALIPSO lidar measurements. The three results are as follows: (1) Average aerosol optical depth (AOD) values during the 14 years were 0.44 and 0.47 during daytime and nighttime, respectively, with an overall decreasing trend, among which the AOD in spring in the southern border region and in winter in the northern border region showed high values, 0.66 and 0.31 during daytime and 0.69 and 0.33 during nighttime, respectively, and nighttime AOD values were higher than those of daytime, possibly due to the lower signal-to-noise ratio of the CALIPSO during the daytime than during the nighttime. (2) The primary representative aerosol type in the Taklamakan Desert region being pure sand and dust, and more apparent winter-polluted sand and dust exist along the northern slope of the Tianshan Mountains in Xinjiang in winter than in other areas. High-altitude soot mainly existed below 4 km and was primarily concentrated in northern Central Asia, with the highest values (0.016 and 0.003) in summer and winter, respectively, which may be due to different diffusion and transport conditions. (3) Dust aerosols in spring were mainly concentrated in the region of 2-6 km in the Taklamakan Desert area; pure dust particles in summer and fall lifted height diffusion and gradually moved to the northern border region; polluted dust was mainly in northern Xinjiang in fall and winter and spread to northern Central Asia; and the average top height of aerosols in the transmission process reached the top of the troposphere, and transmission height was higher than source area.
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Affiliation(s)
- Ying Gan
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
| | - Zhe Zhang
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China; MNR Technology Innovation Center for Central Asia Geo-Information Exploitation and Utilization, Urumqi 830046, China.
| | - Fangqing Liu
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
| | - Zewei Chen
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
| | - Qingfu Guo
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
| | - Zhengnan Zhu
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
| | - Yuxin Ren
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China; Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830046, China
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Yu Y, Taylor PC, Cai M. Seasonal Variations of Arctic Low-Level Clouds and Its Linkage to Sea Ice Seasonal Variations. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2019; 124:12206-12226. [PMID: 32025450 PMCID: PMC6988461 DOI: 10.1029/2019jd031014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 11/01/2019] [Accepted: 11/04/2019] [Indexed: 06/10/2023]
Abstract
Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectrometer data set, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N-82°N) for 2007-2010. A surface-type stratification-consisting Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice-is used to investigate the influence of surface type on low-level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low-level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region (seasonal sea ice zone) by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low-level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and midsummer. We find no significant dependence of the May low-level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low-level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface-atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud-sea ice interactions, a seasonal perspective is critical.
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Affiliation(s)
- Yueyue Yu
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD)/NUIST‐UoR International Research InstituteNanjing University of Information Science and TechnologyNanjingChina
| | | | - Ming Cai
- Department of Earth, Ocean & Atmospheric SciencesFlorida State UniversityTallahasseeFLUSA
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He M, Hu Y, Chen N, Wang D, Huang J, Stamnes K. High cloud coverage over melted areas dominates the impact of clouds on the albedo feedback in the Arctic. Sci Rep 2019; 9:9529. [PMID: 31266977 PMCID: PMC6606566 DOI: 10.1038/s41598-019-44155-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Accepted: 05/01/2019] [Indexed: 11/16/2022] Open
Abstract
Warming in the Arctic is larger than the global average. A primary reason for this Arctic Amplification is the albedo feedback. The contrasting albedo of sea ice and dark melted surface areas is the key component of albedo feedback. Cloud coverage over the changing surface and the response of the clouds to the changing surface conditions will modify the change in planetary albedo when sea ice melts. Space-based lidar measurements provide a unique opportunity for cloud measurements in the Arctic. The response of clouds to the changing sea ice concentration was directly observed. Based on CALIPSO satellite observations of cloud properties, this study found that cloud coverage in ice-free regions in the Arctic linearly increased with the area of ice-free water during the melt seasons in the past 10 years, while sea ice coverage varies significantly year-to-year. The observations suggest that when sea-ice retreats, cloud fraction of the ice-free region remains fixed at nearly 81%. The high cloud coverage over melted areas significantly reduces the albedo feedback. These results indicate that space-based lidar cloud and surface observations of the Arctic can help constrain and improve climate models.
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Affiliation(s)
- Min He
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies; Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Sun Yat-sen University, Zhuhai, 519028, China.,Stevens Institute of Technology, Hoboken, New Jersey, 07030, USA
| | - Yongxiang Hu
- NASA Langley Research Center, MS420, Hampton, Virginia, 23681-2199, USA.
| | - Nan Chen
- Stevens Institute of Technology, Hoboken, New Jersey, 07030, USA
| | - Donghai Wang
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies; Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Sun Yat-sen University, Zhuhai, 519028, China.
| | | | - Knut Stamnes
- Stevens Institute of Technology, Hoboken, New Jersey, 07030, USA
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Thorsen TJ, Kato S, Loeb NG, Rose FG. Observation-Based Decomposition of Radiative Perturbations and Radiative Kernels. JOURNAL OF CLIMATE 2018; 31:10039-10058. [PMID: 35095187 PMCID: PMC8793621 DOI: 10.1175/jcli-d-18-0045.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The Clouds and the Earth's Radiant Energy System (CERES)-partial radiative perturbation [PRP (CERES-PRP)] methodology applies partial-radiative-perturbation-like calculations to observational datasets to directly isolate the individual cloud, atmospheric, and surface property contributions to the variability of the radiation budget. The results of these calculations can further be used to construct radiative kernels. A suite of monthly mean observation-based inputs are used for the radiative transfer, including cloud properties from either the diurnally resolved passive-sensor-based CERES synoptic (SYN) data or the combination of the CloudSat cloud radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar. The CloudSat/CALIPSO cloud profiles are incorporated via a clustering method that obtains monthly mean cloud properties suitable for accurate radiative transfer calculations. The computed fluxes are validated using the TOA fluxes observed by CERES. Applications of the CERES-PRP methodology are demonstrated by computing the individual contributions to the variability of the radiation budget over multiple years and by deriving water vapor radiative kernels. The calculations for the former are used to show that an approximately linear decomposition of the total flux anomalies is achieved. The observation-based water vapor kernels were used to investigate the accuracy of the GCM-based NCAR CAM3.0 water vapor kernel. Differences between our observation-based kernel and the NCAR one are marginally larger than those inferred by previous comparisons among different GCM kernels.
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Affiliation(s)
| | - Seiji Kato
- NASA Langley Research Center, Hampton, Virginia
| | | | - Fred G Rose
- Science System and Applications, Inc., Hampton, Virginia
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Cloud Classification in Wide-Swath Passive Sensor Images Aided by Narrow-Swath Active Sensor Data. REMOTE SENSING 2018. [DOI: 10.3390/rs10060812] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Feasibility of Estimating Cloudy-Sky Surface Longwave Net Radiation Using Satellite-Derived Surface Shortwave Net Radiation. REMOTE SENSING 2018. [DOI: 10.3390/rs10040596] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Ham SH, Kato S, Rose FG, Winker D, L'Ecuyer T, Mace GG, Painemal D, Sun-Mack S, Chen Y, Miller WF. Cloud Occurrences and Cloud Radiative Effects (CREs) from CCCM and CloudSat Radar-Lidar Products. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2017; 122:8852-8884. [PMID: 33868883 PMCID: PMC8051179 DOI: 10.1002/2017jd026725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Two kinds of radar-lidar synergy cloud products are compared and analyzed in this study; CERES-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar (RL) product such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, CCCM has more low-level (< 1 km) clouds over tropical oceans because CCCM uses a more relaxed threshold of Cloud-Aerosol Discrimination (CAD) score for Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask (VFM) product. In contrast, GEOPROF-LIDAR has more mid-level (1-8 km) clouds than CCCM at high latitudes (> 40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar, which may be related to precipitation. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found over three regions. First, CCCM has larger shortwave (SW) and longwave (LW) CREs than FXLHR-LIDAR along the west coasts of Africa and America. This might be caused by missing small-scale marine boundary layer clouds in FLXHR-LIDAR. Second, over tropical oceans where precipitation frequently occurs, SW and LW CREs from FLXHR-LIDAR are larger than those from CCCM partly because FLXHR-LIDAR algorithm includes the contribution of rainwater to total liquid water path. Third, over midlatitude storm-track regions, CCCM shows larger SW and LW CREs than FLXHR-LIDAR, due to CCCM biases caused by larger cloud optical depth or higher cloud effective height.
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Affiliation(s)
- Seung-Hee Ham
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
| | - Seiji Kato
- NASA Langley Research Center, Hampton, Virginia, USA
| | - Fred G Rose
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
| | - David Winker
- NASA Langley Research Center, Hampton, Virginia, USA
| | - Tristan L'Ecuyer
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Gerald G Mace
- Atmospheric Science, University of Utah, Salt Lake City, Utah, USA
| | - David Painemal
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
| | - Sunny Sun-Mack
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
| | - Yan Chen
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
| | - Walter F Miller
- Science Systems and Applications Inc. (SSAI), Hampton, Virginia, USA
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Oreopoulos L, Cho N, Lee D, Kato S. Radiative effects of global MODIS cloud regimes. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2016; 121:2299-2317. [PMID: 29619289 PMCID: PMC5880056 DOI: 10.1002/2015jd024502] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.
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Affiliation(s)
| | - Nayeong Cho
- NASA-GSFC, Earth Science Division, Greenbelt MD 20771 USA
- USRA, Columbia, MD 21044 USA
| | - Dongmin Lee
- NASA-GSFC, Earth Science Division, Greenbelt MD 20771 USA
- Morgan State University, Baltimore MD 21251 USA
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Winker D, Kato S, Tackett J. Global Aerosol Direct Radiative Effect from CALIOP and C3M. EPJ WEB OF CONFERENCES 2016. [DOI: 10.1051/epjconf/201611921001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Barker HW, Kato S, Wehr T. Computation of Solar Radiative Fluxes by 1D and 3D Methods Using Cloudy Atmospheres Inferred from A-train Satellite Data. SURVEYS IN GEOPHYSICS 2011; 33:657-676. [PMID: 26069353 PMCID: PMC4456078 DOI: 10.1007/s10712-011-9164-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2011] [Accepted: 11/15/2011] [Indexed: 06/04/2023]
Abstract
This study used realistic representations of cloudy atmospheres to assess errors in solar flux estimates associated with 1D radiative transfer models. A scene construction algorithm, developed for the EarthCARE mission, was applied to CloudSat, CALIPSO and MODIS satellite data thus producing 3D cloudy atmospheres measuring 61 km wide by 14,000 km long at 1 km grid-spacing. Broadband solar fluxes and radiances were then computed by a Monte Carlo photon transfer model run in both full 3D and 1D independent column approximation modes. Results were averaged into 1,303 (50 km)2 domains. For domains with total cloud fractions Ac < 0.7 top-of-atmosphere (TOA) albedos tend to be largest for 3D transfer with differences increasing with solar zenith angle. Differences are largest for Ac > 0.7 and characterized by small bias yet large random errors. Regardless of Ac , differences between 3D and 1D transfer rarely exceed ±30 W m-2 for net TOA and surface fluxes and ±10 W m-2 for atmospheric absorption. Horizontal fluxes through domain sides depend on Ac with ∼20% of cases exceeding ±30 W m-2; the largest values occur for Ac > 0.7. Conversely, heating rate differences rarely exceed ±20%. As a cursory test of TOA radiative closure, fluxes produced by the 3D model were averaged up to (20 km)2 and compared to values measured by CERES. While relatively little attention was paid to optical properties of ice crystals and surfaces, and aerosols were neglected entirely, ∼30% of the differences between 3D model estimates and measurements fall within ±10 W m-2; this is the target agreement set for EarthCARE. This, coupled with the aforementioned comparison between 3D and 1D transfer, leads to the recommendation that EarthCARE employ a 3D transport model when attempting TOA radiative closure.
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Affiliation(s)
- H. W. Barker
- Cloud Physics and Severe Weather Research Section (ARMP), Environment Canada, 4905 Dufferin St., Toronto, ON M3H 5T4 Canada
| | - S. Kato
- NASA—Langley Research Center, Hampton, VA USA
| | - T. Wehr
- European Space Agency, Noordwijk, The Netherlands
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Sun W, Videen G, Kato S, Lin B, Lukashin C, Hu Y. A study of subvisual clouds and their radiation effect with a synergy of CERES, MODIS, CALIPSO, and AIRS data. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd016422] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Wenbo Sun
- Science Systems and Applications, Inc.; Hampton Virginia USA
- NASA Langley Research Center; Hampton Virginia USA
| | | | - Seiji Kato
- NASA Langley Research Center; Hampton Virginia USA
| | - Bing Lin
- NASA Langley Research Center; Hampton Virginia USA
| | | | - Yongxiang Hu
- NASA Langley Research Center; Hampton Virginia USA
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Kato S, Rose FG, Sun-Mack S, Miller WF, Chen Y, Rutan DA, Stephens GL, Loeb NG, Minnis P, Wielicki BA, Winker DM, Charlock TP, Stackhouse PW, Xu KM, Collins WD. Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd016050] [Citation(s) in RCA: 186] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Cheng A, Xu KM. Improved low-cloud simulation from a multiscale modeling framework with a third-order turbulence closure in its cloud-resolving model component. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd015362] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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